Natural Image-Orientated Hybrid Filter Using Pulse Coupled Neural Network

Abstract

Noise introduced during capture and transmission is inevitable for natural images generated by Complementary Metal-Oxide-Semiconductor (CMOS) sensors, including quantization error during digitalization, transmission disturbance and other sources of noise. To process natural images from a CMOS sensor, a hybrid filter combining Pulse Coupled Neural Network (PCNN), median filter and Wiener filter is proposed in this paper. First, salt-and-pepper noise is located via PCNN, and processed by a median filter. Then, Gaussian noise is removed by a self-adaptive Wiener filter. Simulation results indicated that compared to other methods (hybrid filter containing median and Wiener filter, hybrid filter containing median and wavelet filter), the hybrid filter with PCNN demonstrates better performance in the preservation of image detail and edge in the premise of similar Signal-Noise Ratios (SNRs).